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Results 1 - 10 of 46 for TypeAttr (0.12 sec)
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tensorflow/compiler/mlir/lite/utils/convert_type.h
// Returns element type from attribute Type 'type_attr'. mlir::Type GetShapeStrippedType(mlir::TypeAttr type_attr); // Returns true if 'val' is not from Quantize op or // from Quantize Op with same quant type as 'qtype_attr' bool NotFromQuantOpOrSameQuantType(mlir::Value val, mlir::TypeAttr qtype_attr); } // namespace tflite
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 03 18:01:23 UTC 2024 - 2.1K bytes - Viewed (0) -
tensorflow/c/kernels/bitcast_op_test.cc
Status status; NodeDef def; def.set_op("Bitcast"); def.set_device(DEVICE_CPU); AttrValue typeAttr; SetAttrValue(input_tensor->dtype(), &typeAttr); AttrValue outTypeAttr; SetAttrValue(out_type, &outTypeAttr); (*def.mutable_attr())["T"] = typeAttr; (*def.mutable_attr())["type"] = outTypeAttr; def.add_input(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Jul 18 15:10:51 UTC 2022 - 5.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/device_target.cc
if (!rop) return failure(); llvm::SmallVector<Type, 4> input_specs, out_specs; for (auto spec : rop.getInputSpecs()) { input_specs.push_back(spec.cast<TypeAttr>().getValue()); } for (auto spec : rop.getOutputSpecs()) { out_specs.push_back(spec.cast<TypeAttr>().getValue()); } auto in_spec = input_specs[0].dyn_cast<UniformQuantizedType>(); // TODO(fengliuai): handles the PerAxis QuantizedType.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Mar 08 10:41:08 UTC 2024 - 7.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/utils/lstm_utils.cc
/*asymmetric_quantize_inputs=*/mlir::BoolAttr(), /*input_to_input_intermediate=*/mlir::TypeAttr(), /*input_to_forget_intermediate=*/mlir::TypeAttr(), /*input_to_cell_intermediate=*/mlir::TypeAttr(), /*input_to_output_intermediate=*/mlir::TypeAttr(), /*effective_hidden_scale_intermediate=*/mlir::TypeAttr()); // Cast the static shaped lstm result to FuncOp's signature -
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 36.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/quantization_context.cc
input_specs.push_back(original_input_specs[i]); } else if (requantize.pos == RequantizeState::ON_OUTPUT) { input_specs.push_back(TypeAttr::get(requantize.params)); } else { input_specs.push_back(TypeAttr::get(state.params)); } } op->setAttr("input_specs", ArrayAttr::get(context, input_specs)); llvm::SmallVector<Attribute, 4> output_specs;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Apr 08 01:38:03 UTC 2024 - 13.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/ir/QuantOps.cc
return srcScastOp.getArg(); } /// The quantization specification should match the expressed type. static bool isValidQuantizationSpec(Attribute quantSpec, Type expressed) { if (auto typeAttr = mlir::dyn_cast<TypeAttr>(quantSpec)) { Type spec = typeAttr.getValue(); if (mlir::isa<TensorType, VectorType>(spec)) return false; // The spec should be either a quantized type which is compatible to the
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 5.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/ir/QuantOps.cc
return srcScastOp.getArg(); } /// The quantization specification should match the expressed type. static bool isValidQuantizationSpec(Attribute quantSpec, Type expressed) { if (auto typeAttr = mlir::dyn_cast<TypeAttr>(quantSpec)) { Type spec = typeAttr.getValue(); if (mlir::isa<TensorType, VectorType>(spec)) return false; // The spec should be either a quantized type which is compatible to the
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 5.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/c/c_api_unified_experimental_mlir.cc
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 28.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/prepare_quantize_helper.h
// index. template <typename LstmOp> inline QuantizedType GetIntermediateElementType(LstmOp op, int tensor_index) { if (tensor_index < 0 || tensor_index > 4) return nullptr; TypeAttr attr = op->template getAttrOfType<TypeAttr>( intermediate_attributes[tensor_index]); if (!attr) { return nullptr; } return QuantizedType::getQuantizedElementType(attr.getValue()); }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 03 18:01:23 UTC 2024 - 28K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/tensorflow/tf_to_quant.cc
// folding logic will use a "arith.constant" op to replace the // "tf.FakeQuantWithMinMaxVarsOp", the "tfl.quantize" op is used to preserve // the quantization parameters as a TypeAttr and "tfl.dequantize" op used to // convert the output type to the next op. Here are the transformations: // // input min cst max cst input min cst max cst
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 8.1K bytes - Viewed (0)